Organizations that carry out services in complex operational settings, such as governments, hospitals, banks, companies, and universities, process a tremendous amount of day-to-day transactions. Besides their large scale of daily operations, organizations, especially organizations with mobile workers or workers at multiple sites, such as local governments, including city transportation and public safety organizations, and hospitals, are required to administer various unaccustomed events and circumstances on a daily basis. For example, local governments play roles in various functions, such as city or town development, tourism, public works, parks and recreation, police, fire, emergency services, transportation, housing, and so on. Similarly, services provided by hospitals vary greatly from patient to patient. However, current operating systems for organizations are not capable of recording and classifying all the business operations. For managing such complex business operations, an operating system for organizations must encompass a broad range of operations with due consideration to the changing environment.
Commonly, organizational operating systems are divided into four categories of information systems, such as voice and text messaging systems, workflow systems, data analytics, and structured document collection, and each system carries advantages and disadvantages. First, voice and text messaging systems carry information and coordinate activities in organizations. Email, voicemail, and text messages are usually designed to deliver messages between individuals within an organization by typically specifying a receiver of the messages. Thus, information regarding the messages are usually shared only between the sender and receivers. Even when the context of the message between the sender and the receiver shifts while exchanging messages in one message thread, only the same individuals are involved in the message thread. Manually adding a new receiver into the message thread or specifying a group of individuals as receivers can be an alternative to share the message information with other individuals in the organization but that is not a sufficient solution as an operating system. Further, the message information cannot be processed as data and makes further processing, such as data analytics for aiding organizational activities, difficult.
Secondly, workflow systems orchestrate daily routine operations of the organization into an accessible platform for use by individuals of the organization. The workflow systems break organizational routine operations into smaller tasks so that each individual in the organization can efficiently process and manage a sequence of tasks. However, the workflow system is not adequate to respond to variable and complex environments as the workflow systems are designed for only facilitating routine tasks. In other words, preparing detailed step-by-step decision guidance for responding to complex environments and integrating human observations into the workflow system exceed a capacity of the workflow system.
Further, data analytics present a pattern in data by collecting and statistically processing data. Data analytics can guide organizations in their ongoing operations by reviewing and planning data, usually with visualization. However, data analytics are quantitative and do not generally integrate open-ended, contextual, and unstructured information.
Finally, document collection includes storing documents and metadata in a database and provides file repositories. The stored data in the repositories can be obtained by using a search function. However, for variable types of documents and metadata, generality of the search function is difficult. For example, calendars, spreadsheets, and event planning have special page types. Further, performing data analytics among variable types of data in the database has been unlikely to be successful. Thus, each current operating system falls short for organizations to manage their complex operations.
Structured email systems are disclosed in Malone et al., “The Information Lens: Intelligent Information Sharing Systems,” Communications of the ACM, Vol. 30, No. 5, p. 390-402, May 1986 and Lai et al., “Object Lens: A ‘Spreadsheet’ for Cooperative Work,” ACM Transactions on Office Information Systems, Vol. 6, No. 4, p. 332-353, October 1986, the disclosures of which are incorporated by reference. Emails, such as only formulaic kinds of conversations, are structured for a computer system to access and process data elements.
Comments can be incorporated into analytics, such as described in Heer et al., “Voyagers and Voyeurs: Supporting Asynchronous Collaborative Information Visualization,” Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), Apr. 28-May 3, 2007, San Jose, Calif. Sense.us, which is a system for collaborative visualization, provides a Web-based exploratory analysis framework for U.S. Census data. The Sense.us supports collaboration via commentary threaded conversations via views on data. The comments are connected to the analytics data but do not become a part of data. Similarly, Google Analytics, provided by Google, Inc., Mountain View, Calif., enable to attach comments by users on a visualized analytics data; however, the comments are kept separate from the analytics data.
There is a need for organizing variable unstructured data and incorporating into the analytics data for managing and developing ongoing organizational operations.